Built and Social Environments. Associations with Adolescent Overweight and Activity

Melissa C. Nelson, Penny Gordon-Larsen, Yan Song, Barry M. Popkin

Research output: Contribution to journalArticlepeer-review

215 Scopus citations

Abstract

Background: Little is known about the patterning of neighborhood characteristics, beyond the basic urban, rural, suburban trichotomy, and its impact on physical activity (PA) and overweight. Methods: Nationally representative data (National Longitudinal Study of Adolescent Health, 1994-1995, n =20,745) were collected. Weight, height, PA, and sedentary behavior were self-reported. Using diverse measures of the participants' residential neighborhoods (e.g., socioeconomic status, crime, road type, street connectivity, PA recreation facilities), cluster analyses identified homogeneous groups of adolescents sharing neighborhood characteristics. Poisson regression predicted relative risk (RR) of being physically active (five or more bouts/week of moderate to vigorous PA) and overweight (body mass index equal or greater than the 95th percentile, Centers for Disease Control and Prevention/National Center for Health Statistics growth curves). Results: Six robust neighborhood patterns were identified: (1) rural working class; (2) exurban; (3) newer suburban; (4) upper-middle class, older suburban; (5) mixed-race urban; and (6) low-socioeconomic-status (SES) inner-city areas. Compared to adolescents living in newer suburbs, those in rural working-class (adjusted RR[ARR]=1.38, 95% confidence interval [CI]=1.13-1.69), exurban (ARR=1.30, CI=1.04-1.64), and mixed-race urban (ARR=1.31, CI=1.05-1.64) neighborhoods were more likely to be overweight, independent of individual SES, age, and race/ethnicity. Adolescents living in older suburban areas were more likely to be physically active than residents of newer suburbs (ARR=1.11, CI=1.04-1.18). Those living in low-SES inner-city neighborhoods were more likely to be active, though not significantly so, compared to mixed-race urban residents (ARR=1.09, CI=1.00-1.18). Conclusions: These findings demonstrate disadvantageous associations between specific rural and urban environments and behavior, illustrating important effects of the neighborhood on health and the inherent complexity of assessing residential landscapes across the United States. Simple classical urban-suburban-rural measures mask these important complexities.

Original languageEnglish (US)
Pages (from-to)109-117
Number of pages9
JournalAmerican journal of preventive medicine
Volume31
Issue number2
DOIs
StatePublished - Aug 2006

Bibliographical note

Funding Information:
This research used data from Add Health, a program project designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris, and funded by the NICHD (P01-HD31921), with cooperative funding from 17 other agencies. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Anyone interested in obtaining data files from Add Health should contact Add Health, Carolina Population Center, 123 W. Franklin Street, Chapel Hill NC, 27516-2524 ( www.cpc.unc.edu/addhealth/contract.html ).

Funding Information:
Funding for this study and the development of the preliminary spatial measures comes from the National Institutes of Health, including the National Institute of Child Health and Human Development (NICHD) (R01-HD39183-01, R01 HD041375-01, and K01 HD044263-01), National Institute of Diabetes and Digestive and Kidney Diseases (DK56350), National Institute of Environmental Health Sciences (P30ES10126); a Cooperative Agreement with the Centers for Disease Control and Prevention (CDC SIP 5-00); and a New Investigator Dissertation Award from the Robert Wood Johnson Foundation’s Active Living Research Program (050752). We also thank the Spatial Analysis Unit at the University of North Carolina at Chapel Hill, particularly Phil Page, Jay Stewart, and Evan Hammer, for their assistance in data collection and processing.

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